The Hive-on-Spark project (HIVE-7292) is one of the most watched projects in Apache Hive history. It has attracted developers from across the ecosystem, including from organizations such as Intel, MapR, IBM, and Cloudera, and gained critical help from the Spark community.

The Apache Hive PMC has recently voted to release Hive 1.0.0 (formerly known as Hive 0.14.1).

This release is recognition of the work the Apache Hive community has done over the past nine years and is continuing to do. The Apache Hive 1.0.0 release is a codebase that was expected to be released as 0.14.1 but the community felt it was time to move to a 1.x.y release naming structure.

The community effort to make Apache Spark an execution engine for Apache Hive is making solid progress.

Apache Spark is quickly becoming the programmatic successor to MapReduce for data processing on Apache Hadoop. Over the course of its short history, it has become one of the most popular projects in the Hadoop ecosystem, and is now supported by multiple industry vendors—ensuring its status as an emerging standard.

This new feature, jointly developed by Cloudera and Intel engineers, makes management of role-based security much easier in Apache Hive, Impala, and Hue.

Apache Sentry (incubating) provides centralized authorization for services and applications in the Apache Hadoop ecosystem, allowing administrators to set up granular, role-based protection on resources, and to review them in one place. Previously, Sentry only designated administrators to GRANT and REVOKE privileges on an authorizable object. In Apache Sentry 1.5.0 (shipping inside CDH 5.2), we have implemented a new feature (SENTRY-327) that allows admin users to delegate the GRANT privilege to other users using WITH GRANT OPTION. If a user has the GRANT OPTION privilege on a specific resource, the user can now grant the GRANT privilege to other users on the same resource. Apache Hive, Impala, and Hue have all been updated to take advantage of this new Sentry functionality.

Our thanks to Don Drake (@dondrake), an independent technology consultant who is currently working as a Principal Big Data Consultant at Allstate Insurance, for the guest post below about his experiences with Impala.

It started with a simple request from one of the managers in my group at Allstate to put together a demo of Tableau connecting to Cloudera Impala. I had previously worked on Impala with a large dataset about a year ago while it was still in beta, and was curious to see how Impala had improved since then in features and stability.